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The choroid plexus (ChP) serves as the principal origin of cerebrospinal fluid (CSF). CSF hypersecretion due to ChP inflammation has emerged as an important pathogenesis of hydrocephalus recently. Nevertheless, the precise mechanisms of ChP inflammation and the ensuing CSF hypersecretion in hydrocephalus remain ill-defined. In the present study, we elucidate the critical role of macrophages in the pathogenesis of ChP inflammation. Specifically, we identify the chemokine CCL2, released by ChP epithelial cells, recruits CCR2+ monocytes to the ChP thereby inciting hydrocephalus pathogenesis. The accumulated ChP macrophages increase the inflammation in ChP epithelial cells through TNF-α/TNFR1/NF-κB signaling cascade, thereby leading to CSF hypersecretion. Strikingly, augmentation of ChP‒CCL2 using an adeno-associated viral approach (AAV) exacerbates macrophage recruitment, activation, and ventriculomegaly in rat PHH models. Systemic application of Bindarit, a specific CCL2 inhibitor, significantly inhibits ChP macrophage infiltration and activation and reduces CSF secretion rate. Furthermore, the administration of CCR2 antagonist (INCB 3284) reduces ChP macrophage accumulation and ventriculomegaly. This study not only unveils the ChP CCL2‒CCR2 signaling in the pathophysiology of hydrocephalus but also unveils Bindarit as a promising therapeutic choice for the management of posthemorrhagic hydrocephalus.

Abstract Lymph node metastasis (LNM) is a typical marker in oral squamous cell carcinoma (OSCC) indicating poor prognosis. Pathological examination by artificial image acquisition and analysis, as the main diagnostic method for LNM, often takes a week or longer which may cause great anxiety of the patient and also retard timely treatment. However, there are few efficient fast LNM diagnosis methods in clinical applications currently. Our previous study profiled the proteomics of extracellular vesicles (EVs) derived from postoperative drainage fluid (PDF) and showed the potential of detecting specific EVs that expressed aspartate β-hydroxylase (ASPH) for LNM diagnosis in OSCC patients. Considering that the analysis of ASPH+ PDF-EVs is challenging due to their low abundance (counting less than 10% of total EVs in PDF) and the complex EV isolation process of ultra-centrifugation, we developed a facile platform containing two microfluidic chips filled with antibody-modified microbeads to isolate ASPH+ PDF-EVs, with both the capture and retrieval rate reaching around 90%. Clinical sample analysis based on our method revealed that a mean of 6 × 106 /mL ASPH+ PDF-EVs could be isolated from LNM+ OSCC patients compared to 2.5 × 106 /mL in LNM- OSCC ones. When combined with enzyme-linked immunosorbent assay (ELISA) technique that was commonly used in clinical laboratories in hospitals, this microfluidic platform could precisely distinguish postoperative OSCC patients with LNM or not in several hours, which were validated by a double-blind test containing 6 OSCC patients. We believe this strategy has promise for early diagnosis of LNM in postoperative OSCC patients and finally helps guiding timely and reasonable treatment in clinic.

The in-band full-duplex (IBFD) wireless system is a promising candidate for 6G and beyond, as it can double data throughput and enormously lower transmission latency by supporting simultaneous in-band transmission and reception of signals. Enabling IBFD systems requires a substantial mitigation of a transmitter (Tx)’s strong self-interference (SI) signal into the receiver (Rx) channel. However, current state-of-the-art approaches to tackle this challenge are inefficient in terms of performance, cost, and complexity, hindering the commercialization of IBFD techniques. In this work, we devise and demonstrate an innovative approach to realize IBFD systems that exhibit superior performance with a low-cost and less-complex architecture in an all-passive module. Our scheme is based on meticulously combining polarization-division multiplexing (PDM) with ferromagnetic nonreciprocity to achieve ultra-high isolation between Tx and Rx channels. Such an unprecedented conception has become feasible thanks to a concurrent dual-mode circulator—a new component introduced for the first time—as a key feature of our module, and a dual-mode waveguide that transforms two orthogonally polarized waves into two orthogonal waveguide modes. In addition, we propose a unique passive tunable secondary SI cancellation (SIC) mechanism, which is embedded within the proposed module and boosts the isolation over a relatively broad bandwidth. We report, solely in the analog domain, experimental isolation levels of 50, 70, and 80 dB over 340, 101, and 33 MHz bandwidth at the center frequency of interest, respectively, with excellent tuning capability. Furthermore, the module is tested in two real IBFD scenarios to assess its performance in connection with Tx-to-Rx leakage and modulation error in the presence of a Tx’s strong interference signal.

Abstract Enhancing drought tolerance in crops and understanding the underlying mechanisms have been subject of intense research. The precise function and molecular mechanisms of B-box zinc finger proteins (BBX) remain elusive. Here, we report a natural allele of BBX18 (BBX18 TT ) that encodes a C-terminal truncated protein. While most wild tomato germplasms contain the BBX18 CC allele and show more drought tolerant, modern cultivated tomatoes mostly carry BBX18 TT allele and are more drought sensitive. Knockout of BBX18 leads to improved drought tolerance in transgenic plants of cultivated tomato. Ascorbate peroxidase 1 (APX1) is identified as a BBX18-interacting protein that acts as a positive regulator of drought resistance in tomato. Chromatin immunoprecipitation sequencing analyses reveal that BBX18 binds to a unique cis-acting element of the APX1 promoter and represses its gene expression. This study provides insights into the molecular mechanism underlying drought resistance mediated by the BBX18-APX1 module in plants.

Abstract Circadian rhythms are self-sustaining oscillations within biological systems that play key roles in a diverse multitude of physiological processes. The circadian clock mechanisms in brain and peripheral tissues can oscillate independently or be synchronized/disrupted by external stimuli. Dental enamel is a type of mineralized tissue that forms the exterior surface of the tooth crown. Incremental Retzius lines are readily observable microstructures of mature tooth enamel that indicate the regulation of amelogenesis by circadian rhythms. Teeth enamel is formed by enamel-forming cells known as ameloblasts, which are regulated and orchestrated by the circadian clock during amelogenesis. This review will first examine the key roles of the circadian clock in regulating ameloblasts and amelogenesis. Several physiological processes are involved, including gene expression, cell morphology, metabolic changes, matrix deposition, ion transportation, and mineralization. Next, the potential detrimental effects of circadian rhythm disruption on enamel formation are discussed. Circadian rhythm disruption can directly lead to Enamel Hypoplasia, which might also be a potential causative mechanism of amelogenesis imperfecta. Finally, future research trajectory in this field is extrapolated. It is hoped that this review will inspire more intensive research efforts and provide relevant cues in formulating novel therapeutic strategies for preventing tooth enamel developmental abnormalities.

Genome-scale metabolic models (GEMs) have been widely employed to predict microorganism behaviors. However, GEMs only consider stoichiometric constraints, leading to a linear increase in simulated growth and product yields as substrate uptake rates rise. This divergence from experimental measurements prompted the creation of enzyme-constrained models (ecModels) for various species, successfully enhancing chemical production. Building upon studies that allocate macromolecule resources, we developed a Python-based workflow (ECMpy) that constructs an enzyme-constrained model. This involves directly imposing an enzyme amount constraint in GEM and accounting for protein subunit composition in reactions. However, this procedure demands manual collection of enzyme kinetic parameter information and subunit composition details, making it rather user-unfriendly. In this work, we've enhanced the ECMpy toolbox to version 2.0, broadening its scope to automatically generate ecGEMs for a wider array of organisms. ECMpy 2.0 automates the retrieval of enzyme kinetic parameters and employs machine learning for predicting these parameters, which significantly enhances parameter coverage. Additionally, ECMpy 2.0 introduces common analytical and visualization features for ecModels, rendering computational results more user accessible. Furthermore, ECMpy 2.0 seamlessly integrates three published algorithms that exploit ecModels to uncover potential targets for metabolic engineering. ECMpy 2.0 is available at https://github.com/tibbdc/ECMpy or as a pip package (https://pypi.org/project/ECMpy/).

Abstract A response to the case report by Zhang et al. and supplement another case of giant peritoneal loose body discovered due to abdominal pain. A 68-year-old man was admitted to the hospital with abdominal pain. CT revealed an ovoid mass in the pelvis measuring approximately 11.5 × 8.6 × 7.4 cm. During laparotomy, yellowish-white mass was identified within the pelvis. Histological examination revealed that the mass was hyalinized fibrous connective tissue with focal calcification. We report an extremely rare and interesting case.

Abstract Iron-based Fischer–Tropsch synthesis (FTS) catalyst is widely used for syngas conversion, but its iron carbide active phase is easily oxidized into Fe3O4 by the water produced during reaction, leading to the deterioration of catalytic performance. Here, we show an efficient strategy for protecting the iron carbide active phase of FTS catalyst by surface hydrophobization. The hydrophobic surface can reduce the water concentration in the core vicinity of catalyst during syngas conversion, and thus inhibit the oxidation of iron species by water, which enhances the C − C coupling ability of catalyst and promotes the formation of long-chain olefins. More significantly, it is unraveled that appropriate shell thickness plays a crucial role in stabilizing the iron carbide active phase without Fe3O4 formation and achieving good catalytic performance.

Abstract A body area network involving wearable sensors distributed around the human body can continuously monitor physiological signals, finding applications in personal healthcare and athletic evaluation. Existing solutions for near-field body area networks, while facilitating reliable and secure interconnection among battery-free sensors, face challenges including limited spectral stability against external interference. Here we demonstrate a textile metamaterial featuring a coaxially-shielded internal structure designed to mitigate interference from extraneous loadings. The metamaterial can be patterned onto clothing to form a scalable, customizable network, enabling communication between near-field reading devices and battery-free sensing nodes placed within the network. Proof of concept demonstration shows the metamaterial’s robustness against mechanical deformation and exposure to lossy, conductive saline solutions, underscoring its potential applications in wet environments, particularly in athletic activities involving water or significant perspiration, offering insights for the future development of radio frequency components for a robust body area network at a system level.

Abstract Background Patients with atrial fibrillation (AF) often have coronary artery disease (CAD), but the biological link between them remains unclear. This study aims to explore the common pathogenesis of AF and CAD and identify common biomarkers. Methods Gene expression profiles for AF and stable CAD were downloaded from the Gene Expression Omnibus database. Overlapping genes related to both diseases were identified using weighted gene co-expression network analysis (WGCNA), followed by functional enrichment analysis. Hub genes were then identified using the machine learning algorithm. Immune cell infiltration and correlations with hub genes were explored, followed by drug predictions. Hub gene expression in AF and CAD patients was validated by real-time qPCR. Results We obtained 28 common overlapping genes in AF and stable CAD, mainly enriched in the PI3K-Akt, ECM-receptor interaction, and relaxin signaling pathway. Two hub genes, COL6A3 and FKBP10, were positively correlated with the abundance of MDSC, plasmacytoid dendritic cells, and regulatory T cells in AF and negatively correlated with the abundance of CD56dim natural killer cells in CAD. The AUCs of COL6A3 and FKBP10 were all above or close to 0.7. Drug prediction suggested that collagenase clostridium histolyticum and ocriplasmin, which target COL6A3, may be potential drugs for AF and stable CAD. Additionally, COL6A3 and FKBP10 were upregulated in patients with AF and CAD. Conclusion COL6A3 and FKBP10 may be key biomarkers for AF and CAD, providing new insights into the diagnosis and treatment of this disease.

Abstract. Background:. Although overnight fasting is recommended prior to endoscopic retrograde cholangiopancreatography (ERCP), the benefits and safety of high-carbohydrate fluid diet (CFD) intake 2 h before ERCP remain unclear. This study aimed to analyze whether high-CFD intake 2 h before ERCP can be safe and accelerate patients' recovery. Methods:. This prospective, multicenter, randomized controlled trial involved 15 tertiary ERCP centers. A total of 1330 patients were randomized into CFD group (n = 665) and fasting group (n = 665). The CFD group received 400 mL of maltodextrin orally 2 h before ERCP, while the control group abstained from food/water overnight (>6 h) before ERCP. All ERCP procedures were performed using deep sedation with intravenous propofol. The investigators were blinded but not the patients. The primary outcomes included postoperative fatigue and abdominal pain score, and the secondary outcomes included complications and changes in metabolic indicators. The outcomes were analyzed according to a modified intention-to-treat principle. Results:. The post-ERCP fatigue scores were significantly lower at 4 h (4.1 ± 2.6 vs. 4.8 ± 2.8, t = 4.23, P

Abstract Purpose Some studies have found that the pathological formation of kidney stones is closely related to injury and inflammatory response. Behaviors such as dietary composition, physical activity, obesity and smoking can all affect the body’s oxidative stress levels. In order to evaluate the effects of various diets and lifestyles on the body’s oxidative and antioxidant systems, an oxidative balance score was developed. To investigate whether the OBS is associated with the development of kidney stones. Methods Data were taken from the National Health and Nutrition Examination Survey (NHANES) from 2007–2018, followed by retrospective observational studies. The association between kidney stones and OBS was analyzed using survey-weighted logistic regression by adjusting for demographics, laboratory tests, and medical comorbidity covariates. The oxidative balance score is calculated by screening 16 nutrients and 4 lifestyle factors, including 5 prooxidants and 15 antioxidants, based on prior information about the relationship between oxidation levels in the body and nutrients or lifestyle factors. Results A total of 26,786 adult participants were included in the study, of which 2,578, or 9.62%, had a history of nephrolithiasis. Weighted logistic regression analysis found an association between OBS and kidney stones. In the fully tuned model, i.e., model 3, the highest quartile array of OBS was associated with the lowest quartile array of OBS (OR = 0.73 (0.57, 0.92)) with the risk of kidney stone (p = 0.01), and was statistically significant and remained relatively stable in each model. At the same time, the trend test in the model is also statistically significant. With the increase of OBS, the OR value of kidney stones generally tends to decrease. Conclusions There is an inverse correlation between OBS and kidney stone disease. At the same time, higher OBS suggests that antioxidant exposure is greater than pro-oxidative exposure in diet and lifestyle, and is associated with a lower risk of kidney stones

Abstract Background Smoking induces and modifies the airway immune response, accelerating the decline of asthmatics’ lung function and severely affecting asthma symptoms’ control level. To assess the prognosis of asthmatics who smoke and to provide reasonable recommendations for treatment, we constructed a nomogram prediction model. Methods General and clinical data were collected from April to September 2021 from smoking asthmatics aged ≥14 years attending the People’s Hospital of Zhengzhou University. Patients were followed up regularly by telephone or outpatient visits, and their medication and follow-up visits were recorded during the 6-months follow-up visit, as well as their asthma control levels after 6 months (asthma control questionnaire-5, ACQ-5). The study employed R4.2.2 software to conduct univariate and multivariate logistic regression analyses to identify independent risk factors for ‘poorly controlled asthma’ (ACQ>0.75) as the outcome variable. Subsequently, a nomogram prediction model was constructed. Internal validation was used to test the reproducibility of the model. The model efficacy was evaluated using the consistency index (C-index), receiver operating characteristic (ROC) curve, calibration curve, and decision curve. Results Invitations were sent to 231 asthmatics who smoked. A total of 202 participants responded, resulting in a final total of 190 participants included in the model development. The nomogram established five independent risk factors (P

Proteins play a pivotal role in coordinating the functions of organisms, essentially governing their traits, as the dynamic arrangement of diverse amino acids leads to a multitude of folded configurations within peptide chains. Despite dynamic changes in amino acid composition of an individual protein (referred to as AAP) and great variance in protein expression levels under different conditions, our study, utilizing transcriptomics data from four model organisms uncovers surprising stability in the overall amino acid composition of the total cellular proteins (referred to as AACell). Although this value may vary between different species, we observed no significant differences among distinct strains of the same species. This indicates that organisms enforce system-level constraints to maintain a consistent AACell, even amid fluctuations in AAP and protein expression. Further exploration of this phenomenon promises insights into the intricate mechanisms orchestrating cellular protein expression and adaptation to varying environmental challenges.

Summary: Somatostatin (SOM)-expressing neurons in the central lateral amygdala (CeL) are responsible for fear memory learning, but the circuit and molecular mechanisms underlying this biology remain elusive. Here, we found that glutamatergic neurons in the lateral parabrachial nucleus (LPB) directly dominated the activity of CeLSOM neurons, and that selectively inhibiting the LPBGlu→CeLSOM pathway suppressed fear memory acquisition. By contrast, inhibiting CeL-projecting glutamatergic neurons in the paraventricular thalamic nucleus (PVT) interfered with consolidation-related processes. Notably, CeLSOM-innervating neurons in the LPB were modulated by presynaptic cannabinoid receptor 1 (CB1R), and knock down of CB1Rs in LPB glutamatergic neurons enhanced excitatory transmission to the CeL and partially rescued the impairment in fear memory induced by CB1R activation in the CeL. Overall, our study reveals the mechanisms by which CeLSOM neurons mediate the formation of fear memories during fear conditioning in mice, which may provide a new direction for the clinical research of fear-related disorders.

Abstract The lining structures of tunnels are typically constructed using sprayed or cast concrete materials, and their performance and quality during tunnel excavation and blasting are crucial for the stability and safety of tunnels. Therefore, the safe distance between the lining structure and blasting source should be determined to avoid concrete damage caused by blasting vibrations. In this study, taking the subway tunnel of Danshan Station in Qingdao as an example, the JH-2 model is introduced as the constitutive model of the tunnel blasting simulation, and the JH-2 model parameters of the local surrounding rock are obtained by experiments, and finally the numerical simulation and theoretical verification are carried out to study the safety distance of shotcrete under various safety judgment standards. The results indicate that the JH-2 model can effectively simulate the propagation of stress waves under different media conditions, and the closer the strength parameters and pressure constant of the lining structure are to those of the surrounding rock, the safer the concrete–rock bonding interface. During tunnel blasting construction using the ring blasting method, the peak particle velocity (PPV) of the lining structure increases with an increase in the arch angle. Based on the numerical simulation results, we recommend that concrete lining be constructed at a distance of at least 62 m from the blasting source to avoid damage caused by vibrations. The effect of concrete tensile failure caused by longitudinal stress is much smaller than the damage to the bonding interface caused by the PPV and can be neglected.

Abstract The death of coronavirus disease 2019 (COVID-19) is primarily due to from critically ill patients, especially from ARDS complications caused by SARS-CoV-2. Therefore, it is essential to contribute an in-depth understanding of the pathogenesis of the disease and to identify biomarkers for predicting critically ill patients at the molecular level. Immunogenic cell death (ICD), as a specific variant of regulatory cell death driven by stress, can induce adaptive immune responses against cell death antigens in the host. Studies have confirmed that both innate and adaptive immune pathways are involved in the pathogenesis of SARS-CoV-2 infection. However, the role of ICD in the pathogenesis of severe COVID-19 has rarely been explored. In this study, we systematically evaluated the role of ICD-related genes in COVID-19. We conducted consensus clustering, immune infiltration analysis, and functional enrichment analysis based on ICD differentially expressed genes. The results showed that immune infiltration characteristics were altered in severe and non-severe COVID-19. In addition, we used multiple machine learning methods to screen for five risk genes (KLF5, NSUN7, APH1B, GRB10 and CD4), which are used to predict COVID-19 severity. Finally, we constructed a nomogram to predict the risk of severe COVID-19 based on the classification and recognition model, and validated the model with external data sets. This study provides a valuable direction for the exploration of the pathogenesis and progress of COVID-19, and helps in the early identification of severe cases of COVID-19 to reduce mortality.

Abstract Background Long non-coding RNAs (lncRNAs) are key regulators of the 6-methyladenosine (m6A) epigenetic modification, playing a role in the initiation and progression of tumors. However, the regulatory mechanisms in head and neck squamous cell carcinoma (HNSCC) remain elusive. In this study, we investigated the molecular regulatory mechanisms of the lncRNA RASAL2-AS1 in the occurrence and development of HNSCC tumors. Methods A bioinformatics analysis was conducted to analyze the expression level of RASAL2-AS1 in HNSCC and normal tissues. RASAL2-AS1 mRNA and protein levels were detected using RT-PCR and Western blotting. Wound healing, transwell assays, flow cytometry, M6A dot blot, and RNA immunoprecipitation experiments were conducted to explore the regulatory role of the RASAL2-AS1 and downstream targets METTL14/LIS1 signaling pathway in HNSCC. Immunohistochemical examination was conducted to evaluate the expression of METTL14 and LIS1 in HNSCC and normal tissues. A tumor xenograft model of BALB/c nude mice was established to assess the impact of RASAL2-AS1 on cell proliferation and growth. Results RASAL2-AS1 high expression in HNSCC and cells deteriorated with survival rates of HNSCC. RASAL2-AS1 overexpression in HNSCC accelerated cell migration, colony formation, cell proliferation, cell cycle in S stage, while RASAL2-AS1 knockdown in HNSC cells inhibited cell cycle in G1 stage. After silencing METTL14, the above effects induced by overexpression of the RASAL2-AS1 were reversed. RASAL2-AS1 overexpression prompted LIS1 expression, whereas RASAL2-AS1 silencing reduced LIS1 levels in HNSCC cells, which was confirmed by immunohistological staining. Results demonstrated elevated expression of METTL14 or LIS1 in tongue cancer tissues. Overexpression of RASAL2-AS1 promoted tumor weight and tumor volume, which was counteracted by pcDNA3.1 RASAL2-AS1 plus silencing METTL14 and METTL14 and LIS1 were significantly decreased. Conclusion Our study highlights the functional importance of the LncRNA RASAL2-AS1 in HNSCC and might assist in the development of a prognostic stratification and therapeutic approach. Which regulates HNSCC with the dependence of m6a manner.

Abstract We construct a two-tensor model with order-3 and present its W-representation. Moreover we derive the compact expressions of correlators from the W-representation and analyze the free energy in large N limit. In addition, we establish the correspondence between two colored Dyck walks in the Fredkin spin chain and tree operators in the ring. Based on the classification Dyck walks, we give the number of tree operators with the given level. Furthermore, we show the entanglement scaling of Fredkin spin chain beyond logarithmic scaling in the ordinary critical systems from the viewpoint of tensor model.

Asphalt could suffer hydrothermal ageing in underwater tunnels, which varies its combustion characteristics significantly. The hydrothermally aged asphalt (HA) was comparatively studied with base asphalt (BA) and thermal-oxidatively aged asphalt (TA). Major findings are achieved: (1) The C＝O and S＝O bonds are more abundant in TA/HA than BA. HA contains more prominent –OH and H2O but less substantial aliphatics. And it has lower SO than TA by about 20 %, attributing to the oxygen isolation of aqueous immersion during hydrothermal ageing. (2) Remarkably bimodal heat release rate (HRR) peaks are found for HA, while only unimodal HRR peak is observed for TA/BA. Importantly, the primarily main HRR peak of HA occurs at around 110 s, which exhibits to be earlier than those of TA/BA by over 120 s. Meanwhile, the fire growth rate index (FGRA) of HA is higher than those of TA/BA by more than 15 %, implying that hydrothermal ageing dramatically increases the asphalt's fire risk. (3) Herein, the combustion mechanism of bimodal HRR peaks found for HA is analyzed, attributing to thin-layer boilover effect. This could be supported by plentiful pores observed on the combusted HA via scanning electron microscopy technique.

A dicentric chromosome is an abnormal chromosome with two centromeres on the same chromosome. It has been reported that dicentric chromosomes are specific biomarkers of radiation exposure, but dicentric chromosomes are rarely identified in newborns with multiple congenital anomalies. At 16 weeks of gestation, a 39-year-old pregnant woman (gravida 2, para 1) was referred to the prenatal diagnosis center for genetic counseling. The fetal ultrasonography indicated multiple anomalies. Subsequently, amniocentesis was performed, and the G-banding karyotype analysis showed a rare type of mosaicism. The C-banding karyotype analysis indicated a pseudo-dicentric chromosome X [psu dic (X; 18) (p11.2; p11.2)]. A single-nucleotide polymorphism array (SNP array) revealed three pathogenic copy number variations (CNVs). After genetic counseling, the parents chose to terminate this pregnancy. This study provides new evidence for a better understanding of the diagnosis of dicentric chromosomes and emphasizes on the importance of genetic counseling.

Abstract Metamaterials hold significant promise for enhancing the imaging capabilities of magnetic resonance imaging (MRI) machines as an additive technology, due to their unique ability to enhance local magnetic fields. However, despite their potential, the metamaterials reported in the context of MRI applications have often been impractical. This impracticality arises from their predominantly flat configurations and their susceptibility to shifts in resonance frequencies, preventing them from realizing their optimal performance. Here, a computational method for designing wearable and tunable metamaterials via freeform auxetics is introduced. The proposed computational‐design tools yield an approach to solving the complex circle packing problems in an interactive and efficient manner, thus facilitating the development of deployable metamaterials configured in freeform shapes. With such tools, the developed metamaterials may readily conform to a patient's knee, ankle, head, or any part of the body in need of imaging, and while ensuring an optimal resonance frequency, thereby paving the way for the widespread adoption of metamaterials in clinical MRI applications.

IntroductionLiuweizhiji Gegen-Sangshen beverage (LGS) is popular in China, which has been used for alleviating alcohol-mediated discomfort and preventing alcoholic liver disease (ALD). This beverage is consisted of six herbal components that are known as functional foods and fruits. LGS is rich in polysaccharides, however, the activity and quality evaluation of LGS-derived polysaccharides remain unexplored. The purpose of this study is thus to establish a comprehensive quality control methodology for the assessment of LGS polysaccharides (LGSP) and to further explore the anti-oxidant, anti-inflammatory as well as prebiotic effect of LGSP.MethodsLGSP was extracted, followed by analysis of molecular weight distribution, monosaccharide content and structural characterization via integrating the application of high-performance size exclusion chromatography (HPSEC), 1-phenyl-3-methyl-5-pyrazolone-HPLC (PMP-HPLC), fourier transform infrared spectroscopy (FT-IR) as well as nuclear magnetic resonance spectroscopy (NMR) techniques. The anti-oxidation activity of LGSP was determined by DPPH, ABTS, hydroxyl radical scavenging capacity and total antioxidant capacity. The anti-inflammation of LGSP were assessed on the RAW 264.7 cells. The effect of LGSP on growth of Lactobacillus, Bifidobacterium bifidum and Bifidobacterium adolescentis was evaluated.ResultsThe results demonstrated that LGSP had two molecular weight distribution peaks, with the average molecular weights of (6.569 ± 0.12) × 104 Da and (4.641 ± 0.30) × 104 Da. LGSP was composed of 8 monosaccharides, with galacturonic acid, glucose rhamnose and galactose representing the highest molar ratios. Homogalacturonic acid (HG) type and rhamnosegalacturonic acid glycans I (RG-I) type and α-1,4-glucan were present in LGSP. LGSP concentration in LGS was 17.94 ± 0.28 mg/mL. Furthermore, fingerprint analysis combined with composition quantification of 10 batches of LGSP demonstrated that there was a high similarity among batches. Notably, LGSP exhibited anti-oxidant effect and inhibited expressions of pro-inflammatory factors (TNF-α and IL-6) in LPS-stimulated RAW 264.7 cells. In addition, LGSP remarkably promoted the proliferation of probiotics Lactobacillus, Bifidobacterium bifidum and Bifidobacterium adolescentis, showing good prebiotic activity.DiscussionThe results of present study would be of help to gain the understanding of structure–activity relationship of LGSP, provide a reference for quality evaluation of bioactive LGSP, and facilitate development of unique health and functional products in the future.

Abstract Purpose This study aimed to systematically compare the efficacy and safety of arthroscopic wafer procedure (AWP) versus ulnar shortening osteotomy (USO) for ulnar impaction syndrome (UIS) treatment. Methods All the studies included in this meta-analysis compared the efficacy of AWP to USO for UIS and were acquired through a comprehensive search across multiple databases. The meta-analysis was performed by calculating the effect sizes with the Cochrane Collaboration’s RevMan 5.4 software. Results A total of 8 articles were included in this analysis, comprising 148 cases in the AWP group and 163 cases in the USO group. The pooled estimates indicated no significant differences in combined Darrow’s Criteria or Modified Mayo Wrist Score, Modified Mayo Wrist Score, DASH scores, grip strength, VAS score, and postoperative ulnar variation. On the other hand, the patients in the AWP group exhibited fewer complications (OR = 0.17, 95%CI 0.05–0.54, P = 0.003) and a lower reoperation rate (OR = 0.12, 95%CI 0.05–0.28, P

Beyond 5G and 6G technologies mark a pivotal evolution in the telecommunications landscape. They are not only anticipated to deliver unprecedented speed and capacity but also to serve as critical enablers for a host of emerging technologies and applications, including joint communications and sensing, autonomous driving, augmented reality (AR), virtual reality (VR), and the burgeoning Internet of Things (IoT) [1], [2], [3]. As we transition into this new era, the expectations for system performance, reliability, and versatility are higher than ever before.

Trueperella pyogenes is a significant opportunistic pathogen that causes substantial economic losses in animal agriculture due to its ability to infect various animal tissues and organs. Limited research has been conducted on the prevalence and biological characteristics of T. pyogenes isolated from sheep and goats. This study aimed to isolate T. pyogenes from clinical samples of sheep and goats in western China, examining genetic evolutionary relationships, antibiotic resistance, and virulence genes. Between 2021 and 2023, standard bacteriological methods were used to isolate and identify T. pyogenes from 316 samples (209 from goats and 107 from sheep) collected from 39 farms. Susceptibility to 14 antibiotics was tested using broth microdilution per CLSI guidelines, and PCR detected eight virulence genes. Whole-genome sequencing analyzed genetic relationships and gene carriage status in 39 isolates. The results indicated that 86 strains of T. pyogenes were isolated from 316 samples, yielding an isolation rate of 27.2% (goats n = 47, 22.5%; sheep n = 39, 36.4%). The virulence genes plo, cbpA, nanH, nanP, fimA, fimC, and fimE were present in 100%, 66.7%, 64.1%, 71.8%, 69.2%, 59.0%, and 82.1% of isolates, respectively, with none carrying the fimG gene. The dominant virulence genotype was plo/nanH/nanP/fimA/fimC/fimE. The isolates exhibited resistance to erythromycin (44.2%, 38/86), gentamicin (38.4%, 33/86), sulfamethoxazole/trimethoprim (37.2%, 32/86), tetracycline (32.6%, 28/86), and streptomycin (32.6%, 28/86), and low resistance to chloramphenicol (14.0%, 12/86), ciprofloxacin (7.0%, 6/86), penicillin (5.8%, 5/86), and clindamycin (4.7%, 4/86). All isolates were susceptible to cefotaxime, vancomycin, and linezolid. Among the 86 isolates, 37 (43.0%) displayed multidrug resistance (MDR) characteristics. The whole genome sequencing of 39 isolates identified eight types of resistance genes, including ant(2″)-Ia, ant(3″)-Ia, cmlA1, cmx, erm(X), lnu(A), sul1, and tet(W). Except for tet(W), erm(X), and sul1, the other resistance genes were reported for the first time in T. pyogenes isolated in China. The drug susceptibility test results and resistance gene detection for the isolated strains were consistent for tetracycline, erythromycin, gentamicin, and sulfisoxazole. Similar allelic profiles and genetic evolutionary relationships were found among isolates from different farms. This study highlights the antibiotic resistance status and virulence gene-carrying rate of Trueperella pyogenes, providing a basis for clinical medication.

The concrete used in the main structures of subway stations has a high degree of constraint. Consequently, temperature changes and shrinkage during construction frequently lead to significant constraint stress, which can result in structural cracking. Therefore, cement with low hydration heat is commonly used in engineering to reduce the temperature of concrete during its age. Aiming at the problem of hydration and heat release caused by concrete construction, based on the principles of concrete hydration heat release and a numerical analysis method, an optimized semi-adiabatic temperature rise test method has been introduced to investigate concrete temperature rise characteristics with different mineral admixtures. The following conclusions were obtained: The effect of reducing the heat of hydration is related to the content and material properties of different mineral admixtures, but not the type of mineral admixture to be incorporated. The temperature rise performance of four common mineral admixtures is as follows: ① total cooling capacity: limestone powder > slag, fly ash > metakaolin; ② early heat generation rate: metakaolin > slag > fly ash > limestone powder; ③ heat reduction rate in the middle and late periods: metakaolin > limestone powder > fly ash > slag.

Unmanned aerial vehicles (UAVs) are increasingly deployed to enhance the operational efficiency of city services. However, finding optimal solutions for the gather–return task pattern under dynamic environments and the energy constraints of UAVs remains a challenge, particularly in dense high-rise building areas. This paper investigates the multi-UAV path planning problem, aiming to optimize solutions and enhance data gathering rates by refining exploration strategies. Initially, for the path planning problem, a reinforcement learning (RL) technique equipped with an environment reset strategy is adopted, and the data gathering problem is modeled as a maximization problem. Subsequently, to address the limitations of stationary distribution in indicating the short-term behavioral patterns of agents, a Time-Adaptive Distribution is proposed, which evaluates and optimizes the policy by combining the behavioral characteristics of agents across different time scales. This approach is particularly suitable for the early stages of learning. Furthermore, the paper describes and defines the “Narrow-Elongated Path” Problem (NEP-Problem), a special spatial configuration in RL environments that hinders agents from finding optimal solutions through random exploration. To address this, a Robust-Optimization Exploration Strategy is introduced, leveraging expert knowledge and robust optimization to ensure UAVs can deterministically reach and thoroughly explore any target areas. Finally, extensive simulation experiments validate the effectiveness of the proposed path planning algorithms and comprehensively analyze the impact of different exploration strategies on data gathering efficiency.

Silver–Russell syndrome (SRS) is a clinically and genetically heterogeneous disorder. A retrospective analysis predicted that the live birth prevalence of SRS in Estonia is 1:15,886 [Yakoreva et al., Eur J Hum Genet, 2019, 27(11), 1649–1658]. The most common causative genetic mechanism in the proband is loss of paternal methylation in the imprinted control region 1 (ICR1) at 11p15.5 chromosome. A few studies suggested that inherited or de novo loss-of-function alterations of the PLAG1 gene, including the whole-gene deletion and intragenic pathogenic variants, could cause a rare type of SRS. To date, less than 20 unrelated PLAG1-related SRS cases have been reported, and the clinical information about these cases is limited. We report the first prenatal case of SRS with 8q12 deletion (including the PLAG1 gene). The fetus presented with intrauterine growth retardation, small for gestational age, relative macrocephaly at birth, and a protruding forehead. Unlike classical SRS cases, the fetus had micrognathia and did not show body asymmetry. We hope that the literature review in this study provides new insights into genotype–phenotype relationships of PLAG1-related SRS.

Backgrounds Glioma is a highly aggressive type of brain tumor, and its prognosis is still poor despite recent progress in treatment strategies. G protein-coupled receptor 27 (GPR27) is a member of the G protein-coupled receptor family and has been reported to be involved in various cellular processes, including tumor progression. Nevertheless, the clinical potential and tumor-related role of GPR27 in glioma remain unknown. Here we aimed to explore the function and role of GPR27 in gliomas. Methods In the current study, we evaluated the expression and clinical significance of GPR27 in gliomas using data from The Cancer Genome Atlas (TCGA) datasets. We also conducted cellular experiments to evaluate the functional role of GPR27 in glioma cell growth. Results We found that GPR27 expression level was closely associated with disease status of glioma. Of note, GPR27 was negatively correlated with WHO grade, with grade IV samples showing the lowest GPR27 levels, while grade II samples showed the highest levels. Patients with IDH mutation or 1p/19q co-deletion exhibited higher GPR27 levels. In addition, lower GPR27 levels were correlated with higher death possibilities. In cellular experiments, we confirmed that GPR27 inhibited glioma cell growth. Conclusions Our results indicate that GPR27 may function as a potential prognostic biomarker and therapeutic target in gliomas. Further studies are needed to illustrate the signaling mechanism and clinical implications of GPR27 in gliomas.

Osteosarcoma (OS) is a highly aggressive and lethal malignant bone tumor that primarily afflicts children, adolescents, and young adults. However, the molecular mechanisms underlying OS pathogenesis remain obscure. Mounting evidence implicates dysregulated long non-coding RNAs (lncRNAs) in tumorigenesis and progression. These lncRNAs play a pivotal role in modulating gene expression at diverse epigenetic, transcriptional, and post-transcriptional levels. Uncovering the roles of aberrant lncRNAs would provide new insights into OS pathogenesis and novel tools for its early diagnosis and treatment. In this review, we summarize the significance of lncRNAs in controlling signaling pathways implicated in OS development, including the Wnt/β-catenin, PI3K/AKT/mTOR, NF-κB, Notch, Hippo, and HIF-1α. Moreover, we discuss the multifaceted contributions of lncRNAs to drug resistance in OS, as well as their potential to serve as biomarkers and therapeutic targets. This review aims to encourage further research into lncRNA field and the development of more effective therapeutic strategies for patients with OS.

High-resolution and thermal infrared hyperspectral data acquired from the Thermal Infrared Airborne Spectrographic Imager (TASI) have been recognized as efficient tools in geology, demonstrating significant potential for rock discernment. Deep learning (DL), as an advanced technology, has driven substantial advancements in lithological mapping by automatically extracting high-level semantic features from images to enhance recognition accuracy. However, gathering sufficient high-quality lithological samples for model training is challenging in many scenarios, posing limitations for data-driven DL approaches. Moreover, existing sample collection approaches are plagued by limited verifiability, subjective bias, and variation in the spectra of the same class at different locations. To tackle these challenges, a novel sample generation method called multi-lithology spectra sample selection (MLS3) is first employed. This method involves multiple steps: multiple spectra extraction, spectra combination and optimization, lithological type identification, and sample selection. In this study, the TASI hyperspectral data collected from the Liuyuan area in Gansu Province, China, were used as experimental data. Samples generated based on MLS3 were fed into five typical DL models, including two-dimensional convolutional neural network (2D-CNN), hybrid spectral CNN (HybridSN), multiscale residual network (MSRN), spectral-spatial residual network (SSRN), and spectral partitioning residual network (SPRN) for lithological mapping. Among these models, the accuracy of the SPRN reaches 84.03%, outperforming the other algorithms. Furthermore, MLS3 demonstrates superior performance, achieving an overall accuracy of 2.25–6.96% higher than other sample collection methods when SPRN is used as the DL framework. In general, MLS3 enables both the quantity and quality of samples, providing inspiration for the application of DL to hyperspectral lithological mapping.

Poplar (Populus L.) anthracnose is an infectious disease that seriously affects the growth and yields of poplar trees, and large-scale poplar infections have led to huge economic losses in the Chinese poplar industry. To efficiently and accurately detect poplar anthracnose for improved prevention and control, this study collected hyperspectral data from the leaves of four types of poplar trees, namely healthy trees and those with black spot disease, early-stage anthracnose, and late-stage anthracnose, and constructed a poplar anthracnose detection model based on machine learning and deep learning. We then comprehensively analyzed poplar anthracnose using advanced hyperspectral-based plant disease detection methodologies. Our research focused on establishing a detection model for poplar anthracnose based on small samples, employing the Design of Experiments (DoE)-based entropy weight method to obtain the best preprocessing combination to improve the detection model’s overall performance. We also analyzed the spectral characteristics of poplar anthracnose by comparing typical feature extraction methods (principal component analysis (PCA), variable combination population analysis (VCPA), and the successive projection algorithm (SPA)) with the vegetation index (VI) method (spectral disease indices (SDIs)) for data dimensionality reduction. The results showed notable improvements in the SDI-based model, which achieved 89.86% accuracy. However, this was inferior to the model based on typical feature extraction methods. Nevertheless, it achieved 100% accuracy for early-stage anthracnose and black spot disease in a controlled environment respectively. We conclude that the SDI-based model is suitable for low-cost detection tasks and is the best poplar anthracnose detection model. These findings contribute to the timely detection of poplar growth and will greatly facilitate the forestry sector’s development.

The sea cucumber is an essential nutrient source and a significant economic marine resource associated with successful aquaculture. However, sea cucumbers are highly susceptible to autolysis induced by endogenous protease after postmortem, and the phenomenon of body wall “melting” occurs, which seriously affects the food quality of products and the degree of acceptance by consumers. To satisfy the growing demand for fresh or processed sea cucumbers, we must clarify the autolysis mechanism of sea cucumbers and the methods to achieve autolysis regulation. In this paper, the factors leading to the quality deterioration and texture softening of sea cucumbers are reviewed, with emphasis on enzymatic characteristics, the autolysis mechanism, the effects of autolysis on the physicochemical properties of the body wall of the sea cucumber, and the development of potential natural protease inhibitors. We aim to provide some reference in future preservation and processing processes for sea cucumbers, promote new processing and preservation technologies, and advance the sea cucumber industry’s development.

Coral reef bleaching events have become more frequent all over the world and pose a serious threat to coral reef ecosystems. Therefore, there is an urgent need for better detection of coral reef bleaching in a time- and cost-saving manner. In recent years, remote sensing technology has often been utilized and gained recognition for coral reef bleaching detection. However, bleaching corals in the water always have weak spectral change signals, causing difficulties in using remote sensing data. Additionally, uneven change samples make it challenging to adequately capture the details of coral reef bleaching detection and produce thematic maps. To resolve these problems, a novel method named coral reef bleaching detection by positive-unlabeled bagging (CBD-PUB) is proposed in this paper. To test the capacity of the method, a series of multi-temporal Sentinel-2 remote sensing images are utilized, and Lizard Island in Australia is taken as a case study area. The pseudo-invariant feature atmospheric correction (PIF) algorithm is adopted to improve coral reef bleaching spectral signals. After that, CBD-PUB is employed to effectively explore coral reef bleaching variation and its corresponding influence relations. The experimental results show that the overall accuracy of bleaching detection by the proposed algorithm reaches 92.1% and outperforms the traditional method. It fully demonstrates the feasibility of the model for the field of coral reef bleaching detection and provides assistance in the monitoring and protection of coral environments.

Libration and precession are different body forces that are ubiquitous in many rapidly rotating systems, particularly in geophysical and astrophysical flows. Libration is a modulation of the background rotation magnitude, whereas precession is a modulation of the background rotation direction. Assessing the consequences of these body forces in large-scale flows is challenging. The Ekman number, the ratio of the rotation time scale to the viscous time scale quantifying the rotation speed, is extremely small, leading to extremely thin and intense shear layers in the flows even when the amplitudes of the body forces are very small. We consider the consequences of libration and precession numerically in a geometrically simple container, a cube, which lends itself to very efficient, accurate, and robust numerical treatment, with the axis of rotation passing through opposite vertices, so that all walls of the cube are at oblique angles to the rotation axis. This results in the geometric focusing of inertial wavebeams reflecting off the walls, whereby the energy density of the wavebeams increases along with the magnitude of their wavevector. The nature of this focusing depends on the forcing frequency but not on the body force. In the inviscid setting, wavebeams form infinitesimally thin vortex sheets, and their energy density becomes unbounded upon focusing. We present linear inviscid ray tracing to set the scene for the focusing of wavebeams and then consider viscous problems at an Ekman number that is typical of current state-of-the-art laboratory experiments. We begin by considering the linear responses, which are comprised of focusing viscous shear layers, of which their details are mostly captured via ray tracing, and particular solutions accounting for the body forces. These have complicated spatio-temporal structures, which differ for libration and precession. Increasing the forcing amplitude from zero introduces nonlinear interactions, enhances the focusing effects via vortex tilting and stretching when the shear layers reflect at the walls, and also introduces temporal superharmonics and a mean flow. When the magnitude of the mean flow is within a few percent of the magnitude of the instantaneous flow, instabilities breaking the spatio-temporal symmetries set in. These are localized in the oscillatory boundary layers where the reflections are concentrated and introduce broadband dynamics in the boundary layers, with additional inertial wavebeams emitted into the interior. The details again depend on the specifics of the body forces.

With the development of hyperspectral sensors, the availability of hyperspectral images (HSIs) has increased significantly, prompting advancements in deep learning-based hyperspectral image classification (HSIC) methods. Recently, graph convolutional networks (GCNs) have been proposed to process graph-structured data in non-Euclidean domains, and have been used for HSIC. The superpixel segmentation should be implemented first in the GCN-based methods, however, it is difficult to manually select the optimal superpixel segmentation sizes to obtain the useful information for classification. To solve this problem, we constructed a HSIC model based on a multiscale feature search-based graph convolutional network (MFSGCN) in this study. Firstly, pixel-level features of HSIs are extracted sequentially using 3D asymmetric decomposition convolution and 2D convolution. Then, superpixel-level features at different scales are extracted using multilayer GCNs. Finally, the neural architecture search (NAS) method is used to automatically assign different weights to different scales of superpixel features. Thus, a more discriminative feature map is obtained for classification. Compared with other GCN-based networks, the MFSGCN network can automatically capture features and obtain higher classification accuracy. The proposed MFSGCN model was implemented on three commonly used HSI datasets and compared to some state-of-the-art methods. The results confirm that MFSGCN effectively improves accuracy.

Human papillomavirus (HPV) is a prevalent cause of mucosal and cutaneous infections and underlying conditions ranging from benign warts to anogenital and oropharyngeal cancers affecting both males and females, notably cervical cancer. Cervical cancer is the fourth leading cause of cancer deaths among women globally and is the most impactful in low- and middle-income countries (LMICs), where the costs of screening and licensed L1-based HPV vaccines pose significant barriers to comprehensive administration. Additionally, the licensed L1-based HPV vaccines fail to protect against all oncogenic HPV types. This study generated three independent lots of an L2-based target antigen (LBTA), which was engineered from conserved linear L2-protective epitopes (aa11–88) from five human alphapapillomavirus genotypes in E. coli under cGMP conditions and adjuvanted with aluminum phosphate. Vaccination of rabbits with LBTA generated high neutralizing antibody titers against all 17 HPV types tested, surpassing the nine types covered by Gardasil®9. Passive transfer of naïve mice with LBTA antiserum revealed its capacity to confer protection against vaginal challenge with all 17 αHPV types tested. LBTA shows stability at room temperature over >1 month. Standard in vitro and in vivo toxicology studies suggest a promising safety profile. These findings suggest LBTA’s promise as a next-generation vaccine with comprehensive coverage aimed at reducing the economic and healthcare burden of cervical and other HPV+ cancers in LMICs, and it has received regulatory approval for a first-in-human clinical study (NCT05672966).

Background: Mpox, one of the most serious threats to global health, is now being seen in small but rising numbers in Beijing, China. Our study aimed to investigate healthcare workers’ (HCWs) knowledge of Mpox and to explore reasons associated with their hesitancy to vaccinate against Mpox in Beijing, China. Methods: A cross-sectional study was conducted among HCWs in Beijing from July 24 to August 2, 2023, through an online questionnaire. Participants answered questions about sociodemographic characteristics, Mpox information sources, Mpox knowledge, perception of vaccines, and attitudes toward Mpox vaccination. We used Chi-squared test to compare difference in Mpox vaccination hesitancy between different groups. Multivariable logistic regression models were applied to analyze correlates of vaccination hesitancy among HCWs. Results: A total of 2331 HCWs completed the questionnaire, with an effective response rate of 92.45 % (2155/2331). Most of the HCWs in this study worked at tertiary hospitals (89.65 %), with a mean age of 36.69 ± 9.08 years. Among the 2155 participants, 52.99 % had over ten years of working experience, and 16.66 % were from high-risk departments relevant to Mpox treatment. Approximately 84.41 % knew about Mpox before this study, 80.79 % exhibited a high level of knowledge about Mpox, whereas 42.37 % were hesitant to be vaccinated against Mpox. Moreover, the hesitancy rate of HCWs in high-risk departments (47.91 %) was higher than in lower-risk departments (41.26 %). Higher educational level (aOR = 1.75, 95 %CI: 1.17–2.62), longer working years (1.71, 1.32–2.22), working at high-risk departments (1.34, 1.05–1.71), and lower level of knowledge about Mpox (1.78, 1.13–2.85) appeared as the most significant determinants of Mpox vaccination hesitancy among HCWs who knew about Mpox. For the HCWs who did not know about Mpox, longer working years (1.96, 1.02–3.78) were significant factors associated with their hesitancy. The predominant reason for hesitancy toward Mpox vaccination among HCWs encompassed apprehensions about vaccine side effects. Conclusion: HCWs had good knowledge of Mpox, whereas their Mpox vaccination hesitancy was also relatively high in Beijing, China. Increasing HCWs’ vaccination confidence and knowledge level about Mpox, especially for those working in high-risk departments, may be an essential way of reducing their hesitancy.

We present higher Chern-Simons-Antoniadis-Savvidy (ChSAS) forms based on crossed modules. We start from introducing a generalized multilinear symmetric invariant polynomial for the differential crossed modules and constructing a metric independent, higher gauge invariant, and closed form using the higher curvature forms. Then, we establish the higher Chern-Weil theorem and prove that the higher ChSAS forms are a special case of this theorem. Finally, we get the link of two independent higher ChSAS theories.

In this study, a method for the active shape control for carbon fiber-reinforced polymer (CFRC) reflectors using piezoelectric lead zirconate titanate (PZT) actuators is proposed. According to this method, a finite element model considering higher transverse shear deformation with independent voltage degrees of freedom is formulated by the Hamilton principle. An optimal shape controller that minimizes the discrete root mean square (RMS) error of a reflecting surface is applied. Then, the optimal arrangements of the PZT actuators are determined by numerical optimization methods, which are developed by modifying the classical Genetic Algorithm, with both single and multi-objective optimizations being studied. In the single optimization formulation, the number of actuators is considered as a constraint, and the RMS error of the reflector is regarded as the optimizing target. A hybrid method that combines the gradient projection method with an adaptive Genetic Algorithm is proposed to solve this problem. In the multi-objective optimization, the residual RMS errors and power consumption of the actuators are considered as the optimization targets. Pareto optimal solutions are obtained by an improved multi-objective Genetic Algorithm. Numerical examples are provided to show the effectiveness of the proposed methods.

The interplay between the immune system and cancer underscores the central role of immunotherapy in cancer treatment. In this context, the innate immune system plays a critical role in preventing tumor invasion. Myeloid differentiation factor 88 (MyD88) is crucial for innate immunity, and activation of MyD88 promotes the production of inflammatory cytokines and induces infiltration, polarization, and immune escape of immune cells in the tumor microenvironment. Additionally, abnormal MyD88 signaling induces tumor cell proliferation and metastasis, which are closely associated with poor prognosis. Therefore, MyD88 could serve as a novel tumor biomarker and is a promising target for cancer therapy. Current strategies targeting MyD88 including inhibition of signaling pathways and protein multimerization, have made substantial progress, especially in inflammatory diseases and chronic inflammation-induced cancers. However, the specific role of MyD88 in regulating tumor immunity and tumorigenic mechanisms remains unclear. Therefore, this review describes the involvement of MyD88 in tumor immune escape and disease therapy. In addition, classical and non-classical MyD88 inhibitors were collated to provide insights into potential cancer treatment strategies. Despite several challenges and complexities, targeting MyD88 is a promising avenue for improving cancer treatment and has the potential to revolutionize patient outcomes.

The molecular weight (MW) of an enzyme is a critical parameter in enzyme-constrained models (ecModels). It is determined by two factors: the presence of subunits and the abundance of each subunit. Although the number of subunits (NS) can potentially be obtained from UniProt, this information is not readily available for most proteins. In this study, we addressed this gap by extracting and curating subunit information from the UniProt database to establish a robust benchmark dataset. Subsequently, we propose a novel model named DeepSub, which leverages the protein language model and Bi-directional Gated Recurrent Unit (GRU), to predict NS in homo-oligomers solely based on protein sequences. DeepSub demonstrates remarkable accuracy, achieving an accuracy rate as high as 0.967, surpassing the performance of QUEEN. To validate the effectiveness of DeepSub, we performed predictions for protein homo-oligomers that have been reported in the literature but are not documented in the UniProt database. Examples include homoserine dehydrogenase from Corynebacterium glutamicum, Matrilin-4 from Mus musculus and Homo sapiens, and the Multimerins protein family from M. musculus and H. sapiens. The predicted results align closely with the reported findings in the literature, underscoring the reliability and utility of DeepSub.

In order to improve the simulation efficiency under the premise of ensuring the fidelity of synthetic aperture radar (SAR) simulation images, we propose a BVH-assisted fast SAR image simulation method based on spatial segmentation. The beam scanning model is established based on RD imaging geometric relation, and the bounding volume hierarchy (BVH) algorithm is used to assist in obtaining the time-varying latticed radiation and shadow areas within the radar beam, combining them with the real-time position of the sensors to complete the simulation of the electromagnetic (EM) wave transmission. The ray tracing algorithm is used to calculate the multiple backscatter fields of EM waves, including various material properties of the target surface. The SAR spatial traversal is adopted to spatially segment the latticed radiation area, and the compute unified device architecture (CUDA) kernel function is designed using the echo matrix cell method to make each cell of the target echo matrix as a subfield of the backscattering field, and the position of the echo matrix cell is traversed to obtain the target backscattering field. The target simulated echo is processed by the range Doppler (RD) imaging algorithm to obtain the SAR-simulated image. The simulation results show that compared with a CPU single-thread simulation, the simulation speed of the proposed method is significantly improved, and the SAR simulation image has high structural similarity with the real image, which fully verifies the effectiveness of the proposed method.

The aim of this study was to investigate if the supplementation of folic acid and taurine can relieve the adverse effects of different levels of heat stress (HS) on growth performance, physiological indices, antioxidative capacity, immunity, rumen fermentation and microbiota. A total of 24 Dorper × Hu crossbred lambs (27.51 ± 0.96 kg) were divided into four groups: control group (C, 25 °C), moderate HS group (MHS, 35 °C), severe HS group (SHS, 40 °C), and the treatment group, under severe HS (RHS, 40 °C, 4 and 40 mg/kg BW/d coated folic acid and taurine, respectively). Results showed that, compared with Group C, HS significantly decreased the ADG of lambs (p < 0.05), and the ADG in the RHS group was markedly higher than in the MHS and SHS group (p < 0.05). HS had significant detrimental effects on physiological indices, antioxidative indices and immune status on the 4th day (p < 0.05). The physiological indices, such as RR and ST, increased significantly (p < 0.05) with the HS level and were significantly decreased in the RHS group, compared to the SHS group (p < 0.05). HS induced the significant increase of MDA, TNF-α, and IL-β, and the decrease of T-AOC, SOD, GPx, IL-10, IL-13, IgA, IgG, and IgM (p < 0.05). However, there was a significant improvement in these indices after the supplementation of folic acid and taurine under HS. Moreover, there were a significant increase in Quinella and Succinivibrio, and an evident decrease of the genera Rikenellaceae_RC9_gut_group and Asteroleplasma under HS (p < 0.05). The LEfSe analysis showed that the genera Butyrivibrio, Eubacterium_ventriosum_group, and f_Bifidobacteriaceae were enriched in the MHS, SHS and RHS groups, respectively. Correlated analysis indicated that the genus Rikenellaceae_RC9_gut_group was positively associated with MDA, while it was negatively involved in IL-10, IgA, IgM, and SOD (p < 0.05); The genus Anaeroplasma was positively associated with the propionate and valerate, while the genus Succinivibrio was negatively involved in TNF-α (p < 0.05). In conclusion, folic acid and taurine may alleviate the adverse effects of HS on antioxidant capacity, immunomodulation, and rumen fermentation of lambs by inducing changes in the microbiome that improve animal growth performance.

The concrete of the main structure of subway stations is highly constrained, so the temperature effect and shrinkage effect generated during the construction process often cause large restraint stress, thus causing the problem of structural cracking. Therefore, low-heat-of-hydration cements are usually used in such construction work to reduce the temperature during the aging of concrete. Therefore, based on the hydration heat release subprogram of concrete, an effective numerical simulation was carried out, and compared with the semi-adiabatic temperature rise test, a method of numerical calculation and parameter fitting to solve the influence coefficient of the hydration heat model was proposed, and the sensitivity of the hydration heat release model and the influence coefficient for several concrete mixtures with additives was studied. The main conclusions are as follows: (1) Combined with the measured temperature curves of several types of mineral-admixed concrete, the composite exponential exothermic model of several types of mineral-admixed concrete can be obtained by adjusting the parameter fitting to solve the influence coefficient of the exothermic hydration model proposed in this paper. (2) One can adjust the influencing coefficient a to control the maximum temperature of concrete. Similarly, the temperature curve of concrete can be adjusted by modifying the influencing coefficient b.

Cultivating tourists’ environmental responsibility behavior is an effective way to relieve the pressure of ecological environment in tourist destinations. Based on the value-attitude-behavior theory, this paper constructs a relationship model of values, ecotourism attitude, social responsibility awareness and environmental responsibility behavior, and explores the mechanism of tourists’ values influence on environmental responsibility behavior. Taking three scenic areas (Mao’er Mountain, Yulong River and Xingping Ancient Town) in the Lijiang River Basin of Guilin, a world-famous tourist destination in China, as a case study, the structural equation model is used to test the theoretical hypotheses of tourists’ environmental responsibility behavior. The results of the three studies show that values have a significant positive impact on tourists’ environmental responsibility behavior, while ecotourism attitude cannot directly affect tourists’ environmental responsibility behavior, but values can indirectly affect tourists’ environmental responsibility behavior through the chain intermediary of ecotourism attitude and social responsibility awareness. The findings of the study can effectively guide tourists’ environmental responsibility behavior, which has far-reaching significance for the sustainable development of tourist destinations.